Senior Quality Engineer – Generative AI & Enterprise Web Platforms

Senior Quality Engineer – Generative AI & Enterprise Web Platforms This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office.

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

Job Family Definition: Designs, develops, troubleshoots and debugs software programs for software enhancements and new products. Develops software including operating systems, compilers, routers, networks, utilities, databases and Internet-related tools. Determines hardware compatibility and/or influences hardware design. Management Level Definition: Contributions impact technical components of HPE products, solutions, or services regularly and sustainable. Applies advanced subject matter knowledge to solve complex business issues and is regarded as a subject matter expert. Provides expertise and partnership to functional and technical project teams and may participate in cross-functional initiatives. Exercises significant independent judgment to determine best method for achieving objectives. May provide team leadership and mentoring to others.

Quality strategy and governance: Define risk-based test strategies, quality gates, release criteria, traceability, and measurable objectives across AI, UI, API, cloud, and network layers. Generative AI and agent validation: Evaluate model quality, groundedness, safety, privacy, robustness, tool use, permissions, failure recovery, latency, and cost. Application and integration testing: Validate React interfaces, web standards, accessibility, security, APIs, asynchronous workflows, and enterprise integrations. Cloud, network, and resilience testing: Test AWS deployments, distributed systems, traffic behaviour, scaling, failover, disaster recovery, and adverse network conditions. Performance and automation: Build reusable Python and pytest frameworks and execute performance, scale, reliability, and end-to-end testing with CI/CD integration. Production quality and continuous improvement: Use telemetry, incidents, and user feedback to detect regressions, strengthen coverage, and improve preventive controls. Collaboration and quality leadership: Partner across disciplines, use AI-assisted testing responsibly, mentor engineers, and promote shared ownership of quality.

Required: Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related discipline 10 years’ experience with 3 years in a lead role Knowledge and Skills: Quality strategy and governance: Define risk-based test strategies, quality gates, release criteria, traceability, and measurable objectives across AI, UI, API, cloud, and network layers. Generative AI and agent validation: Evaluate model quality, groundedness, safety, privacy, robustness, tool use, permissions, failure recovery, latency, and cost. Application and integration testing: Validate React interfaces, web standards, accessibility, security, APIs, asynchronous workflows, and enterprise integrations. Cloud, network, and resilience testing: Test AWS deployments, distributed systems, traffic behaviour, scaling, failover, disaster recovery, and adverse network conditions. Performance and automation: Build reusable Python and pytest frameworks and execute performance, scale, reliability,